Police Dyads Within an Operational Simulation: an Empirical Test of the Research Propositions Made in the “Big Five” Teamwork Approach

Based on the impact of the theoretical big five of teamwork model proposed by Salas et al. (2005), the present study aimed at investigating the model within an operational police simulation. One hundred and sixty-seven frontline police officers participated in the study. Based on path analyses, a reduced model excluding trust and leadership obtained a good fit with the data. The results provided some support for the model by confirming six out of 10 proposed direct effects and four out of seven indirect pathways. Shared mental models directly affected team adaptability, and backup behavior affects adaptability and team effectiveness. Team orientation affects mutual performance monitoring and backup behavior, and finally, reciprocal monitoring affects backup behavior. Monitoring influenced both team effectiveness and adaptability through backup behavior. Two paths from team orientation towards effectiveness were found. One flowing through monitoring and another through back-up behavior. Our study expands former knowledge of the big five theory by empirically testing the totality of the model and identifying important pathways.publishedVersio

Big Data - Bigger Responsibility?

Purpose: To investigate whether there is a correlation between consumers’ knowledge about the phenomenon of Big Data and their attitude towards it, and also if the attitude is reflected in their behaviour. Furthermore, the purpose is to find out how different companies usage of Big Data affects consumers’ attitude towards those brands, in a situation where they know what Big Data means. Methodology: We conducted a qualitative focus group and a quantitative survey. We used an interpretation perspective when studying the focus group and an analytical perspective for the quantitative survey, to be able to investigate the correlations and analyze the experiment. For this reason we have an abductive methodology where the text alternates between theory and empirical data, influenced by each other. Theoretical perspective: Consumer Behaviour, Ethical dilemmas, Corporate Identity, Brand attitude, the Stakeholder Model, Customer Relationship Management (CRM), Panopticon. Empirical foundation: Based on a focus group with five participants who all have an interest in Internet-related subjects, but with varying levels of knowledge concerning such subjects. It is also based on a survey with 297 respondents that where not chosen from any particular group of individuals, since it was solely a test of correlations. Conclusion: Individuals with a high level of knowledge about Big Data have a more positive attitude towards it. People with the opposite, a low level of knowledge, show a more negative attitude towards Big Data. Regardless of the level of knowledge or attitude, everyone tends to recognize that there are privacy risks. When a consumer knows what Big Data means they also tend to be negative towards companies that use Big Data. The level of negative affection in consumers’ attitude towards brands that use Big Data varies between companies, which could depend on the different industry they operate in. Companies must start informing consumers about how they work to protect the privacy, otherwise they risk an increase in negative attitude towards the brand

Modified of UTAUT theory in adoption of technology for Malaysia Small Medium Enterprises (SMEs) in food industry

A small and medium enterprise is a backbone of local and world economy including Malaysia as developing country. It is estimated that over 90 percent of all enterprises are SMEs and the contribution from SMEs is more than 70 percent of goods and services sold worldwide. Food industry is mainly dominated by SMEs, even though SMEs of food industry is huge contribution towards economies. Moreover, Malaysian SMEs are still rely on imported food and use of technology adoption has been spike issues among SMEs as they require a big outlay which lacking resources to SMEs. However, SMEs of food industry in Malaysia could be improve their competitive advantage through the increasing level of use technology and provide training to enhance more skills of employees. Moreover, the introducing of Unified theory of acceptance and use of technology (UTAUT) is one option for SMEs to increase quality of products and simultaneously enhance the contribution of good domestic product and export activity. This study will attempt to analyze the acceptance and use of technology in SMEs of food industry in order to understand the SMEs behavior towards acceptance and use of higher level of technology. A model developed and empirically tested through survey data obtained from 135 organizations. This model was analyzed using SPSS and test exploratory factor analysis. The result indicates effort expectancy has been removing and this study decides to replace this construct resistance to use. Thus, this study contributes to existing literature by incorporating resistance of use of new construct UTAUT theory as a proposed model

Technological and human factors for supporting big data analytics in Saudi Arabian higher education

© 2020 26th Americas Conference on Information Systems, AMCIS 2020. All rights reserved. Big data analytics is an emerging technology that is widely utilized across industries and is increasingly discussed among researchers. This study investigates the effects of Technological and Human Factors for Big Data Analytics (THFFBDA) on technological improvements of big data analytics (BDA) towards improved decision making by top management in Saudis' Higher Education. This paper seeks to enhance our understanding of how these components impact on the implementation of big data analytics to improve decision making by top management in Saudi Arabian Higher Institutions. This study draws on the Sociotechnical theory to define and investigate THFFBDA, and the Delone & McLean Information System success model to highlight the technological improvements in BDA. This research paper concludes with propositions on the potential effects of THFFBDA on decision making among universities' top management and proposes a mixed-methods approach to study the above phenomenon

Defining Honesty: A Qualitative Analysis of the Trait Honesty

A popular theoretical model in personality psychology is the Five Factor Model, or the Big Five. This model is structured to have five superordinate factors; Extraversion, Agreeableness, Conscientious, Neuroticism, and Openness (McCrae & Costa, 2003). Each of these factors includes numerous facets that contribute to each of the superordinate traits. However, there is some controversy over what these facets incorporate. For example, Agreeableness, according consists of straightforwardness, altruism, compliance, modesty, and tender-mindedness (Costa & McCrae, 1995). However, the factor of Agreeableness, as defined by the Big Five Model, lacks an important personality variable: honesty. Honesty can be conceptualized as acting in a manner consistent with ones values and beliefs in addition to telling the truth. It is displayed by someone who has a tendency to be fair and genuine towards others (Hilbig, Zettler, & Heydasch, 2011). Honesty has been viewed to be an important personality trait, as evidenced by honesty being consistently listed as one of the most desirable qualities in a romantic partner (citation). If honesty is such an important personality trait, it should be incorporated into a well-established model of personality. Although the Big Five does not incorporate honesty into the model, a different personality theory, the HEXACO (Honesty-Humility, Emotionality, eXtraversion, Agreeableness (versus Anger), Conscientiousness, Openness to Experience) model, has emerged which does factor in honesty. This theory is based on the lexical approach using data from different languages. The HEXACO model incorporates a sixth factor in addition to the factors included in the Big Five model. This additional trait has been labeled Honesty-Humility, which has been shown to be related to Agreeableness (Ashton & Lee, 2005). Research has shown that this model, with the inclusion of the Honesty-Humility trait, explains incremental variance beyond the classical five‐factor approach (Hilbig, Zettler, & Heydasch, 2011). Although the lexical approach, which investigates the importance of personality traits by looking at the presence of descriptive words for the trait within a given language (citation – I think Allport but double check), is a decent start, it does not address how individuals conceptualize the trait. The lexical approach only investigates whether or not there is a word present in language to explain the trait. Therefore, although the HEXACO model is a decent start at understanding the trait of honesty, it is important to investigate how regular people conceptualize honesty using empirical methods. Consequently, we used open-ended questions as a framework for identifying major themes related to the trait of honesty in the current study. 85 undergraduates participated in the online survey in exchange for course credit. The survey consisted of 8 open-ended questions inquiring into participants perceptions of honesty in addition to demographic questions. These questions asked participants to describe both honest and dishonest situations, as well as the qualities that both honest and dishonest people have. Therefore, we were able to address both individual differences and situational factors that contribute to the conceptualization of honesty. 12 members of the research team read through the responses and identified major themes and commonalities of honesty and dishonesty. The next step for this project is to create a quantitative measure of honesty based on the major themes generated from the open-ended questions and to determine how well this new measure aligns with the measure of honesty developed for the HEXACO model in addition to the Big Five Factor of Agreeableness. By incorporating how individuals conceptualize honesty into the development of the scale, we will be better able to understand the construct through further research

Bulgarian Youth and Europe. Multivariate Psycho-cultural Study of the Mobility Attitudes

The objective of this study is to examine the Bulgarian youths' mobility towards Europe. The investigation was carried out with 570 Bulgarian students. The data are presented as a questionnaire consisting of five parts. The first one deals with the motivations and is based on the Reversal Theory - predicting eight motivational states. The second part is based on the 2PAP theoretical model structuring the attitudes around four factors: Push, Pull, Anti Push and Anti Pull. The third one falls back on the Big Five Personality Test measuring five personality dimensions. And the concluding two parts are designed to obtain information about the degree of attraction and the intentions for mobility to the 25 destination countries of the European Union (EU). This has led to the hypothesis that a model of mobility exists based on these three theoretical models, as well as on emotional factors like attraction-repulsion to the country referred to. The hypothesis that was strongly supported by the statistical processing of the data will broaden our understanding of the youth's mobility. The present research is a part of a longitudinal study of the mobility intentions among young people. The investigation is of great interest from an educational, political and social point of vie

Hybrid user perception model: comparing users’ perceptions toward collaborative, content-based, and hybrid recommender systems

This study examines users’ perceptions toward three types of recommender systems by employing a hybrid user perception model combining with Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) in order to specifically explain a message-attitude-use process. Recommender systems, as an innovation applying big data ideas and algorithmic power, have been widely applied to multiple Internet industries. In order to further investigate how users perceived the use of recommender systems and the differences among users’ perceptions toward the use of different recommender systems (collaborative filtering, content-based filtering, and hybrid filtering), three perception variables (perceived usefulness, perceived behavioral control, and perceived enjoyment) were specifically assessed by using an online survey of college students. Overall, the results indicated that there were some statistically significant differences among the user perceptions towards different types of recommender systems. In addition, users generally feel positive about the use of these recommender systems, and users’ perceptions toward hybrid-filtering system were rated higher than perceptions toward collaborative filtering and content-based filtering

Smart construction companies using internet of things technologies

The digital world is enriched due to the increase in the number of things which are rapidly connecting to the Internet. The Internet of Things (IoT) facilitates and improves the work efficiency and human life in various fields. IoT was adopted extensively to male buildings more effective and extra smart. For example, buildings are consuming a considerable energy amount. In buildings, there is a critical requirement for energy efficiency, whereas one of the smart building’s aims is monitoring, reducing and managing the energy consumption of buildings without compromising the operational efficiency and the comfort of occupants. The systems of Heating, Ventilation and Air Conditioning (HVAC) are contributing to considerable consumption of energy in buildings. Also, plug loads and lighting are consuming a lot energy. Thus, smart buildings have the ability of using many IoT sensor types in HVAC along with other mechanical systems making such more adaptive and intelligent. The embedded sensors as well as their related controllers which are mounted in smart buildings are generating a huge amount of data (big data), such data might be subjected to extraction, filtration ana analyzation and utilized for the analytics of smart buildings. For example, the big data analytics might be utilized for analyzing and improving the energy efficiency in addition to the residents’ overall user experience in building. It has been verified that there is an increased focus on smart buildings and big data analytics and management. Yet, there is a requirement for identifying the problems and solutions for overcoming them in such field. With the use of a design research method and model driven architecture, this study aims to develop such system.The major aim of this work is introducing a technique with increased possibility for moving Intelligent Buildings (IBs) towards next-generation model. It depends on IoT adapted to IB for integrating smart re-configurable subsystems and components of IB into Enterprise Network Integrated Building Systems (ENIBSs), also, if possible, into ENIBS’ global networks. The study is presented in the following way. Section 2 is providing an overview of IoT, it is indicating that IoT is relatively new and no associated contribution on using the IoT on IBs or, on the ENIBSs, were indicated in such regard. Section3 is presenting the methodological model that has been used to design a generic model for the IoT with the applicability in the IBs as well as generic architectures for re-configurable smart plug-and-play control systems for quick configuration and integration regarding smart components of the IB. Section 4 provides the theory’ experimental test. The study ends up with the conclusions and some suggestions for the future work